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Safe and Efficient Navigation in Extreme Environments using Semantic Belief Graphs | https://ieeexplore.ieee.org/document/10161056/ | [
"Muhammad Fadhil Ginting",
"Sung-Kyun Kim",
"Oriana Peltzer",
"Joshua Ott",
"Sunggoo Jung",
"Mykel J. Kochenderfer",
"Ali-akbar Agha-mohammadi",
"Muhammad Fadhil Ginting",
"Sung-Kyun Kim",
"Oriana Peltzer",
"Joshua Ott",
"Sunggoo Jung",
"Mykel J. Kochenderfer",
"Ali-akbar Agha-mohammadi"
] | To achieve autonomy in unknown and unstruc-tured environments, we propose a method for semantic-based planning under perceptual uncertainty. This capability is cru-cial for safe and efficient robot navigation in environment with mobility-stressing elements that require terrain-specific locomotion policies. We propose the Semantic Belief Graph (SBG), a geometric- and semantic-based representation o... |
Risk-Aware Neural Navigation From BEV Input for Interactive Driving | https://ieeexplore.ieee.org/document/10161473/ | [
"Suzanna Jiwani",
"Xiao Li",
"Sertac Karaman",
"Daniela Rus",
"Suzanna Jiwani",
"Xiao Li",
"Sertac Karaman",
"Daniela Rus"
] | Safety has been a key goal for autonomous driving since its inception, and we believe recognizing and responding to risk is a key component of safety. In this work, we aim to answer the question, “How can explainable risk representations be generated and used to produce risk-averse trajectories?” To answer this question, previous work uses risk metrics to formulate an optimization problem. In cont... |
Informable Multi-Objective and Multi-Directional RRT* System for Robot Path Planning | https://ieeexplore.ieee.org/document/10160838/ | [
"Jiunn-Kai Huang",
"Yingwen Tan",
"Dongmyeong Lee",
"Vishnu R. Desaraju",
"Jessy W. Grizzle",
"Jiunn-Kai Huang",
"Yingwen Tan",
"Dongmyeong Lee",
"Vishnu R. Desaraju",
"Jessy W. Grizzle"
] | Multi-objective or multi-destination path planning is crucial for mobile robotics applications such as mobility as a service, robotics inspection, and electric vehicle charging for long trips. This work proposes an anytime iterative system to concurrently solve the multi-objective path planning problem and determine the visiting order of destinations. The system is comprised of an anytime informab... |
Leveraging Scene Embeddings for Gradient-Based Motion Planning in Latent Space | https://ieeexplore.ieee.org/document/10161427/ | [
"Jun Yamada",
"Chia-Man Hung",
"Jack Collins",
"Ioannis Havoutis",
"Ingmar Posner",
"Jun Yamada",
"Chia-Man Hung",
"Jack Collins",
"Ioannis Havoutis",
"Ingmar Posner"
] | Motion planning framed as optimisation in structured latent spaces has recently emerged as competitive with traditional methods in terms of planning success while significantly outperforming them in terms of computational speed. However, the real-world applicability of recent work in this domain remains limited by the need to express obstacle information directly in state-space, involving simple g... |
Sample-Driven Connectivity Learning for Motion Planning in Narrow Passages | https://ieeexplore.ieee.org/document/10161339/ | [
"Sihui Li",
"Neil T. Dantam",
"Sihui Li",
"Neil T. Dantam"
] | Sampling-based motion planning works well in many cases but is less effective if the configuration space has narrow passages. In this paper, we propose a learning-based strategy to sample in these narrow passages, which improves overall planning time. Our algorithm first learns from the configuration space planning graphs and then uses the learned information to effectively generate narrow passage... |
Online Coverage Path Planning Scheme for a Size-Variable Robot | https://ieeexplore.ieee.org/document/10160733/ | [
"M. A. Viraj J. Muthugala",
"S. M. Bhagya P. Samarakoon",
"Mohan Rajesh Elara",
"M. A. Viraj J. Muthugala",
"S. M. Bhagya P. Samarakoon",
"Mohan Rajesh Elara"
] | Coverage Path Planning (CPP) is an essential feature of robots deployed for applications such as lawn mowing, cleaning, painting, and exploration. However, most of the state-of-the-art CPP methods are proposed for fixed-morphology robots, and the coverage performance is limited by physical constraints such as the inaccessibility of narrow spaces. Apart from area coverage, productivity depends on c... |
Navigation with polytopes and B-spline path planner | https://ieeexplore.ieee.org/document/10160561/ | [
"Ngoc Thinh Nguyen",
"Pranav Tej Gangavarapu",
"Arne Sahrhage",
"Georg Schildbach",
"Floris Ernst",
"Ngoc Thinh Nguyen",
"Pranav Tej Gangavarapu",
"Arne Sahrhage",
"Georg Schildbach",
"Floris Ernst"
] | This paper firstly presents our optimal path planning algorithm within a $2\mathrm{D}$ non-convex, polytopic region defined as a sequence of connected convex polytopes. The path is a B-spline curve but being parametrized with its equivalent Bézier representation. By doing this, the local convexity bound of each curve's interval is significantly tighter. Thus, it allows many more possibilities for ... |
Probabilistic Planning with Partially Ordered Preferences over Temporal Goals | https://ieeexplore.ieee.org/document/10160678/ | [
"Hazhar Rahmani",
"Abhishek N. Kulkarni",
"Jie Fu",
"Hazhar Rahmani",
"Abhishek N. Kulkarni",
"Jie Fu"
] | In this paper, we study planning in stochastic systems, modeled as Markov decision processes (MDPs), with preferences over temporally extended goals. Prior work on temporal planning with preferences assumes that the user preferences form a total order, meaning that every pair of outcomes are comparable with each other. In this work, we consider the case where the preferences over possible outcomes... |
A causal decoupling approach to efficient planning for logistics problems with stateful stochastic demand | https://ieeexplore.ieee.org/document/10160544/ | [
"Diptanil Chaudhuri",
"Dylan A. Shell",
"Diptanil Chaudhuri",
"Dylan A. Shell"
] | Future conceptions of agile, just-in-time fabrication, lean and “smart” manufacturing, and a host of allied processes that exploit advanced automation, depend in part on realizing improvements in logistics planning. The present paper hypothesizes that the key to improving flexibility will be the inclusion of sophisticated, time-correlated stochastic models of demand—whether that be demand by end-u... |
Stochastic Robustness Interval for Motion Planning with Signal Temporal Logic | https://ieeexplore.ieee.org/document/10161409/ | [
"Roland B. Ilyes",
"Qi Heng Ho",
"Morteza Lahijanian",
"Roland B. Ilyes",
"Qi Heng Ho",
"Morteza Lahijanian"
] | In this work, we present a novel robustness measure for continuous-time stochastic trajectories with respect to Signal Temporal Logic (STL) specifications. We show the soundness of the measure and develop a monitor for reasoning about partial trajectories. Using this monitor, we introduce an STL sampling-based motion planning algorithm for robots under uncertainty. Given a minimum robustness requi... |
Planning with SiMBA: Motion Planning under Uncertainty for Temporal Goals using Simplified Belief Guides | https://ieeexplore.ieee.org/document/10160897/ | [
"Qi Heng Ho",
"Zachary N. Sunberg",
"Morteza Lahijanian",
"Qi Heng Ho",
"Zachary N. Sunberg",
"Morteza Lahijanian"
] | This paper presents a new multi-layered algorithm for motion planning under motion and sensing uncertainties for Linear Temporal Logic specifications. We propose a technique to guide a sampling-based search tree in the combined task and belief space using trajectories from a simplified model of the system, to make the problem computationally tractable. Our method eliminates the need to construct f... |
RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation | https://ieeexplore.ieee.org/document/10160602/ | [
"Lakshay Sharma",
"Michael Everett",
"Donggun Lee",
"Xiaoyi Cai",
"Philip Osteen",
"Jonathan P. How",
"Lakshay Sharma",
"Michael Everett",
"Donggun Lee",
"Xiaoyi Cai",
"Philip Osteen",
"Jonathan P. How"
] | A key challenge in fast ground robot navigation in 3D terrain is balancing robot speed and safety. Recent work has shown that 2.5D maps (2D representations with additional 3D information) are ideal for real-time safe and fast planning. However, the prevalent approach of generating 2D occupancy grids through raytracing makes the generated map unsafe to plan in, due to inaccurate representation of u... |
Prioritized Robotic Exploration with Deadlines: A Comparison of Greedy, Orienteering, and Profitable Tour Approaches | https://ieeexplore.ieee.org/document/10161118/ | [
"Sayantan Datta",
"Srinivas Akella",
"Sayantan Datta",
"Srinivas Akella"
] | This paper addresses the problem of robotic exploration of unknown indoor environments with deadlines. Indoor exploration using mobile robots has typically focused on exploring the entire environment without considering deadlines. The objective of the prioritized exploration in this paper is to rapidly compute the geometric layout of an initially unknown environment by exploring key regions of the... |
Epistemic Prediction and Planning with Implicit Coordination for Multi-Robot Teams in Communication Restricted Environments | https://ieeexplore.ieee.org/document/10161553/ | [
"Lauren Bramblett",
"Shijie Gao",
"Nicola Bezzo",
"Lauren Bramblett",
"Shijie Gao",
"Nicola Bezzo"
] | In communication restricted environments, a multi-robot system can be deployed to either: i) maintain constant communication but potentially sacrifice operational efficiency due to proximity constraints or ii) allow disconnections to increase environmental coverage efficiency, challenges on how, when, and where to reconnect (rendezvous problem). In this work we tackle the latter problem and notice... |
Uncertainty-Guided Active Reinforcement Learning with Bayesian Neural Networks | https://ieeexplore.ieee.org/document/10160686/ | [
"Xinyang Wu",
"Mohamed El-Shamouty",
"Christof Nitsche",
"Marco F. Huber",
"Xinyang Wu",
"Mohamed El-Shamouty",
"Christof Nitsche",
"Marco F. Huber"
] | Recent advances in Reinforcement Learning (RL) have made significant contributions in past years by offering intelligent solutions to solve robotic tasks. However, most RL algorithms, especially the model-free RL, are plagued by low learning efficiency and safety problems. In this paper, we propose using the Bayesian Neural Networks (BNNs) to guide the agent exploring actively to enhance the learn... |
Perturbation-Based Best Arm Identification for Efficient Task Planning with Monte-Carlo Tree Search | https://ieeexplore.ieee.org/document/10161169/ | [
"Daejong Jin",
"Juhan Park",
"Kyungjae Lee",
"Daejong Jin",
"Juhan Park",
"Kyungjae Lee"
] | Combining task and motion planning (TAMP) is crucial for intelligent robots to perform complex and long-horizon tasks. In TAMP, many approaches generally employ Monte-Carlo tree search (MCTS) with upper confidence bound (UCB) for task planning to handle exploration-exploitation trade-off and find globally optimal solutions. However, since UCB basically considers the estimation error caused by nois... |
Contingency-Aware Task Assignment and Scheduling for Human-Robot Teams | https://ieeexplore.ieee.org/document/10160806/ | [
"Neel Dhanaraj",
"Santosh V. Narayan",
"Stefanos Nikolaidis",
"Satyandra K. Gupta",
"Neel Dhanaraj",
"Santosh V. Narayan",
"Stefanos Nikolaidis",
"Satyandra K. Gupta"
] | We consider the problem of task assignment and scheduling for human-robot teams to enable the efficient completion of complex problems, such as satellite assembly. In high-mix, low volume settings, we must enable the human-robot team to handle uncertainty due to changing task requirements, potential failures, and delays to maintain task completion efficiency. We make two contributions: (1) we acco... |
Extracting generalizable skills from a single plan execution using abstraction-critical state detection | https://ieeexplore.ieee.org/document/10161270/ | [
"Khen Elimelech",
"Lydia E. Kavraki",
"Moshe Y. Vardi",
"Khen Elimelech",
"Lydia E. Kavraki",
"Moshe Y. Vardi"
] | Robotic task planning is computationally challenging. To reduce planning cost and support life-long operation, we must leverage prior planning experience. To this end, we address the problem of extracting reusable and generalizable abstract skills from successful plan executions. In previous work, we introduced a supporting framework, allowing us, theoretically, to extract an abstract skill from a... |
Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction | https://ieeexplore.ieee.org/document/10161517/ | [
"Steve Paul",
"Wenyuan Li",
"Brian Smyth",
"Yuzhou Chen",
"Yulia Gel",
"Souma Chowdhury",
"Steve Paul",
"Wenyuan Li",
"Brian Smyth",
"Yuzhou Chen",
"Yulia Gel",
"Souma Chowdhury"
] | Efficient multi-robot task allocation (MRTA) is fundamental to various time-sensitive applications such as disaster response, warehouse operations, and construction. This paper tackles a particular class of these problems that we call MRTA-collective transport or MRTA-CT - here tasks present varying workloads and deadlines, and robots are subject to flight range, communication range, and payload c... |
On the Utility of Buffers in Pick-n-Swap Based Lattice Rearrangement | https://ieeexplore.ieee.org/document/10161182/ | [
"Kai Gao",
"Jingjin Yu",
"Kai Gao",
"Jingjin Yu"
] | We investigate the utility of employing multiple buffers in solving a class of rearrangement problems with pick- n-swap manipulation primitives. In this problem, objects stored randomly in a lattice are to be sorted using a robot arm with k 1 swap spaces or buffers, capable of holding up to $k$ objects on its end-effector simultaneously. On the structural side, we show that the addition of each ne... |
On-Demand Multi-Agent Basket Picking for Shopping Stores | https://ieeexplore.ieee.org/document/10160398/ | [
"Mattias Tiger",
"David Bergström",
"Simon Wijk Stranius",
"Evelina Holmgren",
"Daniel de Leng",
"Fredrik Heintz",
"Mattias Tiger",
"David Bergström",
"Simon Wijk Stranius",
"Evelina Holmgren",
"Daniel de Leng",
"Fredrik Heintz"
] | Imagine placing an online order on your way to the grocery store, then being able to pick the collected basket upon arrival or shortly after. Likewise, imagine placing any online retail order, made ready for pickup in minutes instead of days. In order to realize such a low-latency automatic warehouse logistics system, solvers must be made to be basket-aware. That is, it is more important that the ... |
Multi-Robot Coordination and Cooperation with Task Precedence Relationships | https://ieeexplore.ieee.org/document/10160998/ | [
"Walker Gosrich",
"Siddharth Mayya",
"Saaketh Narayan",
"Matthew Malencia",
"Saurav Agarwal",
"Vijay Kumar",
"Walker Gosrich",
"Siddharth Mayya",
"Saaketh Narayan",
"Matthew Malencia",
"Saurav Agarwal",
"Vijay Kumar"
] | We propose a new formulation for the multi-robot task planning and allocation problem that incorporates (a) precedence relationships between tasks; (b) coordination for tasks allowing multiple robots to achieve increased efficiency; and (c) cooperation through the formation of robot coalitions for tasks that cannot be performed by individual robots alone. In our formulation, the tasks and the rela... |
On the programming effort required to generate Behavior Trees and Finite State Machines for robotic applications | https://ieeexplore.ieee.org/document/10160972/ | [
"Matteo Iovino",
"Julian Förster",
"Pietro Falco",
"Jen Jen Chung",
"Roland Siegwart",
"Christian Smith",
"Matteo Iovino",
"Julian Förster",
"Pietro Falco",
"Jen Jen Chung",
"Roland Siegwart",
"Christian Smith"
] | In this paper we provide a practical demonstration of how the modularity in a Behavior Tree (BT) decreases the effort in programming a robot task when compared to a Finite State Machine (FSM). In recent years the way to represent a task plan to control an autonomous agent has been shifting from the standard FSM towards BTs. Many works in the literature have highlighted and proven the benefits of s... |
Train What You Know – Precise Pick-and-Place with Transporter Networks | https://ieeexplore.ieee.org/document/10161242/ | [
"Gergely Sóti",
"Xi Huang",
"Christian Wurll",
"Björn Hein",
"Gergely Sóti",
"Xi Huang",
"Christian Wurll",
"Björn Hein"
] | Precise pick-and-place is essential in robotic applications. To this end, we define an exact training method and an iterative inference method that improve pick-and-place precision with Transporter Networks [1]. We conduct a large scale experiment on 8 simulated tasks. A systematic analysis shows, that the proposed modifications have a significant positive effect on model performance. Considering ... |
Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation | https://ieeexplore.ieee.org/document/10161004/ | [
"Cem Gokmen",
"Daniel Ho",
"Mohi Khansari",
"Cem Gokmen",
"Daniel Ho",
"Mohi Khansari"
] | Recent progress in end-to-end Imitation Learning approaches has shown promising results and generalization capabilities on mobile manipulation tasks. Such models are seeing increasing deployment in real-world settings, where scaling up requires robots to be able to operate with high autonomy, i.e. requiring as little human supervision as possible. In order to avoid the need for one-on-one human su... |
Seq2Seq Imitation Learning for Tactile Feedback-based Manipulation | https://ieeexplore.ieee.org/document/10161145/ | [
"Wenyan Yang",
"Alexandre Angleraud",
"Roel S. Pieters",
"Joni Pajarinen",
"Joni-Kristian Kämäräinen",
"Wenyan Yang",
"Alexandre Angleraud",
"Roel S. Pieters",
"Joni Pajarinen",
"Joni-Kristian Kämäräinen"
] | Robot control for tactile feedback based manip-ulation can be difficult due to modeling of physical contacts, partial observability of the environment, and noise in perception and control. This work focuses on solving partial observability of contact-rich manipulation tasks as a Sequence-to-Sequence (Seq2Seq) Imitation Learning (IL) problem. The proposed Seq2Seq model first produces a robot-enviro... |
SGTM 2.0: Autonomously Untangling Long Cables using Interactive Perception | https://ieeexplore.ieee.org/document/10160574/ | [
"Kaushik Shivakumar",
"Vainavi Viswanath",
"Anrui Gu",
"Yahav Avigal",
"Justin Kerr",
"Jeffrey Ichnowski",
"Richard Cheng",
"Thomas Kollar",
"Ken Goldberg",
"Kaushik Shivakumar",
"Vainavi Viswanath",
"Anrui Gu",
"Yahav Avigal",
"Justin Kerr",
"Jeffrey Ichnowski",
"Richard Cheng",
"Thomas Kollar",
"Ken Goldberg"
] | Cables are commonplace in homes, hospitals, and industrial warehouses and are prone to tangling. This paper extends prior work on autonomously untangling long cables by introducing novel uncertainty quantification metrics and actions that interact with the cable to reduce perception uncertainty. We present Sliding and Grasping for Tangle Manipulation 2.0 (SGTM 2.0), a system that autonomously unta... |
Online Tool Selection with Learned Grasp Prediction Models | https://ieeexplore.ieee.org/document/10160952/ | [
"Khashayar Rohanimanesh",
"Jake Metzger",
"William Richards",
"Aviv Tamar",
"Khashayar Rohanimanesh",
"Jake Metzger",
"William Richards",
"Aviv Tamar"
] | Deep learning-based grasp prediction models have become an industry standard for robotic bin-picking systems. To maximize pick success, production environments are often equipped with several end-effector tools that can be swapped on-the-fly, based on the target object. Tool-change, however, takes time. Choosing the order of grasps to perform, and corresponding tool-change actions, can improve sys... |
FOGL: Federated Object Grasping Learning | https://ieeexplore.ieee.org/document/10161191/ | [
"Seok–Kyu Kang",
"Changhyun Choi",
"Seok–Kyu Kang",
"Changhyun Choi"
] | Federated learning is a promising technique for training global models in a data-decentralized environment. In this paper, we propose a federated learning approach for robotic object grasping. The main challenge is that the data collected by multiple robots deployed in different environments tends to form heterogeneous data distributions (i.e., non-IID) and that the existing federated learning met... |
Goal-Image Conditioned Dynamic Cable Manipulation through Bayesian Inference and Multi-Objective Black-Box Optimization | https://ieeexplore.ieee.org/document/10160884/ | [
"Kuniyuki Takahashi",
"Tadahiro Taniguchi",
"Kuniyuki Takahashi",
"Tadahiro Taniguchi"
] | To perform dynamic cable manipulation to realize the configuration specified by a target image, we formulate dynamic cable manipulation as a stochastic forward model. Then, we propose a method to handle uncertainty by maximizing the expectation, which also considers estimation errors of the trained model. To avoid issues like multiple local minima and requirement of differentiability by gradient-b... |
Learning Generalizable Pivoting Skills | https://ieeexplore.ieee.org/document/10161271/ | [
"Xiang Zhang",
"Siddarth Jain",
"Baichuan Huang",
"Masayoshi Tomizuka",
"Diego Romeres",
"Xiang Zhang",
"Siddarth Jain",
"Baichuan Huang",
"Masayoshi Tomizuka",
"Diego Romeres"
] | The skill of pivoting an object with a robotic system is challenging for the external forces that act on the system, mainly given by contact interaction. The complexity increases when the same skills are required to generalize across different objects. This paper proposes a framework for learning robust and generalizable pivoting skills, which consists of three steps. First, we learn a pivoting po... |
Cloth Funnels: Canonicalized-Alignment for Multi-Purpose Garment Manipulation | https://ieeexplore.ieee.org/document/10161546/ | [
"Alper Canberk",
"Cheng Chi",
"Huy Ha",
"Benjamin Burchfiel",
"Eric Cousineau",
"Siyuan Feng",
"Shuran Song",
"Alper Canberk",
"Cheng Chi",
"Huy Ha",
"Benjamin Burchfiel",
"Eric Cousineau",
"Siyuan Feng",
"Shuran Song"
] | Automating garment manipulation is challenging due to extremely high variability in object configurations. To reduce this intrinsic variation, we introduce the task of “canonicalized-alignment” that simplifies downstream applications by reducing the possible garment configurations. This task can be considered as “cloth state funnel” that manipulates arbitrarily configured clothing items into a pre... |
RLAfford: End-to-End Affordance Learning for Robotic Manipulation | https://ieeexplore.ieee.org/document/10161571/ | [
"Yiran Geng",
"Boshi An",
"Haoran Geng",
"Yuanpei Chen",
"Yaodong Yang",
"Hao Dong",
"Yiran Geng",
"Boshi An",
"Haoran Geng",
"Yuanpei Chen",
"Yaodong Yang",
"Hao Dong"
] | Learning to manipulate 3D objects in an interactive environment has been a challenging problem in Reinforcement Learning (RL). In particular, it is hard to train a policy that can generalize over objects with different semantic categories, diverse shape geometry and versatile functionality. In this study, we focused on the contact information in manipulation processes, and proposed a unified repre... |
Implementation and Optimization of Grasping Learning with Dual-modal Soft Gripper | https://ieeexplore.ieee.org/document/10161249/ | [
"Lei Zhao",
"Haoyue Liu",
"Feihan Li",
"Xingyu Ding",
"Yuhao Sun",
"Fuchun Sun",
"Jianhua Shan",
"Qi Ye",
"Lincheng Li",
"Bin Fang",
"Lei Zhao",
"Haoyue Liu",
"Feihan Li",
"Xingyu Ding",
"Yuhao Sun",
"Fuchun Sun",
"Jianhua Shan",
"Qi Ye",
"Lincheng Li",
"Bin Fang"
] | Robust and efficient grasping of different objects is still an open problem due to the difficulty of integrating multidisciplinary knowledge such as gripper ontology design, perception, control, and learning. In recent years, learning-based methods have achieved excellent results in grasping various novel objects. However, current methods are usually limited to a single grasping mode or rely on di... |
DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets | https://ieeexplore.ieee.org/document/10160986/ | [
"Isabella Huang",
"Yashraj Narang",
"Ruzena Bajcsy",
"Fabio Ramos",
"Tucker Hermans",
"Dieter Fox",
"Isabella Huang",
"Yashraj Narang",
"Ruzena Bajcsy",
"Fabio Ramos",
"Tucker Hermans",
"Dieter Fox"
] | Robotic grasping of 3D deformable objects is critical for real-world applications such as food handling and robotic surgery. Unlike rigid and articulated objects, 3D deformable objects have infinite degrees of freedom. Fully defining their state requires 3D deformation and stress fields, which are exceptionally difficult to analytically compute or experimentally measure. Thus, evaluating grasp can... |
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control | https://ieeexplore.ieee.org/document/10160374/ | [
"Jiayu Chen",
"Tian Lan",
"Vaneet Aggarwal",
"Jiayu Chen",
"Tian Lan",
"Vaneet Aggarwal"
] | Hierarchical Imitation Learning (HIL) has been proposed to recover highly-complex behaviors in long-horizon tasks from expert demonstrations by modeling the task hierarchy with the option framework. Existing methods either overlook the causal relationship between the subtask and its corresponding policy or cannot learn the policy in an end-to-end fashion, which leads to suboptimality. In this work... |
Efficiently Learning Small Policies for Locomotion and Manipulation | https://ieeexplore.ieee.org/document/10160791/ | [
"Shashank Hegde",
"Gaurav S. Sukhatme",
"Shashank Hegde",
"Gaurav S. Sukhatme"
] | Neural control of memory-constrained, agile robots requires small, yet highly performant models. We leverage graph hyper networks to learn graph hyper policies trained with off-policy reinforcement learning resulting in networks that are two orders of magnitude smaller than commonly used networks yet encode policies comparable to those encoded by much larger networks trained on the same task. We s... |
Learning Agent-Aware Affordances for Closed-Loop Interaction with Articulated Objects | https://ieeexplore.ieee.org/document/10160747/ | [
"Giulio Schiavi",
"Paula Wulkop",
"Giuseppe Rizzi",
"Lionel Ott",
"Roland Siegwart",
"Jen Jen Chung",
"Giulio Schiavi",
"Paula Wulkop",
"Giuseppe Rizzi",
"Lionel Ott",
"Roland Siegwart",
"Jen Jen Chung"
] | Interactions with articulated objects are a challenging but important task for mobile robots. To tackle this challenge, we propose a novel closed-loop control pipeline, which integrates manipulation priors from affordance estimation with sampling-based whole-body control. We introduce the concept of agent-aware affordances which fully reflect the agent's capabilities and embodiment and we show tha... |
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion | https://ieeexplore.ieee.org/document/10161569/ | [
"Julen Urain",
"Niklas Funk",
"Jan Peters",
"Georgia Chalvatzaki",
"Julen Urain",
"Niklas Funk",
"Jan Peters",
"Georgia Chalvatzaki"
] | Multi-objective optimization problems are ubiquitous in robotics, e.g., the optimization of a robot manipulation task requires a joint consideration of grasp pose configurations, collisions and joint limits. While some demands can be easily hand-designed, e.g., the smoothness of a trajectory, several task-specific objectives need to be learned from data. This work introduces a method for learning ... |
Focused Adaptation of Dynamics Models for Deformable Object Manipulation | https://ieeexplore.ieee.org/document/10161366/ | [
"Peter Mitrano",
"Alex LaGrassa",
"Oliver Kroemer",
"Dmitry Berenson",
"Peter Mitrano",
"Alex LaGrassa",
"Oliver Kroemer",
"Dmitry Berenson"
] | In order to efficiently learn a dynamics model for a task in a new environment, one can adapt a model learned in a similar source environment. However, existing adaptation methods can fail when the target dataset contains transitions where the dynamics are very different from the source environment. For example, the source environment dynamics could be of a rope manipulated in free space, whereas ... |
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance | https://ieeexplore.ieee.org/document/10161493/ | [
"Kelvin Xu",
"Zheyuan Hu",
"Ria Doshi",
"Aaron Rovinsky",
"Vikash Kumar",
"Abhishek Gupta",
"Sergey Levine",
"Kelvin Xu",
"Zheyuan Hu",
"Ria Doshi",
"Aaron Rovinsky",
"Vikash Kumar",
"Abhishek Gupta",
"Sergey Levine"
] | Complex and contact-rich robotic manipulation tasks, particularly those that involve multi-fingered hands and underactuated object manipulation, present a significant challenge to any control method. Methods based on reinforcement learning offer an appealing choice for such settings, as they can enable robots to learn to delicately balance contact forces and dexterously reposition objects without ... |
Predicting Motion Plans for Articulating Everyday Objects | https://ieeexplore.ieee.org/document/10160752/ | [
"Arjun Gupta",
"Max E. Shepherd",
"Saurabh Gupta",
"Arjun Gupta",
"Max E. Shepherd",
"Saurabh Gupta"
] | Mobile manipulation tasks such as opening a door, pulling open a drawer, or lifting a toilet seat require constrained motion of the end-effector under environmental and task constraints. This, coupled with partial information in novel environments, makes it challenging to employ classical motion planning approaches at test time. Our key insight is to cast it as a learning problem to leverage past ... |
Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation | https://ieeexplore.ieee.org/document/10160275/ | [
"Sridhar Pandian Arunachalam",
"Sneha Silwal",
"Ben Evans",
"Lerrel Pinto",
"Sridhar Pandian Arunachalam",
"Sneha Silwal",
"Ben Evans",
"Lerrel Pinto"
] | Optimizing behaviors for dexterous manipulation has been a longstanding challenge in robotics, with a variety of methods from model-based control to model-free reinforcement learning having been previously explored in literature. Such prior work often require extensive trial-and-error training along with task-specific tuning of reward functions, which makes applying dexterous manipulation for gene... |
Holo-Dex: Teaching Dexterity with Immersive Mixed Reality | https://ieeexplore.ieee.org/document/10160547/ | [
"Sridhar Pandian Arunachalam",
"Irmak Güzey",
"Soumith Chintala",
"Lerrel Pinto",
"Sridhar Pandian Arunachalam",
"Irmak Güzey",
"Soumith Chintala",
"Lerrel Pinto"
] | A fundamental challenge in teaching robots is to provide an effective interface for human teachers to demonstrate useful skills to a robot. This challenge is exacerbated in dexterous manipulation, where teaching high-dimensional, contact-rich behaviors often require esoteric teleoperation tools. In this work, we present Holo − Dex, a framework for dexter-ous manipulation that places a teacher in a... |
Online augmentation of learned grasp sequence policies for more adaptable and data-efficient in-hand manipulation | https://ieeexplore.ieee.org/document/10161003/ | [
"Ethan K. Gordon",
"Rana Soltani Zarrin",
"Ethan K. Gordon",
"Rana Soltani Zarrin"
] | When using a tool, the grasps used for picking it up, reposing, and holding it in a suitable pose for the desired task could be distinct. Therefore, a key challenge for autonomous in-hand tool manipulation is finding a sequence of grasps that facilitates every step of the tool use process while continuously maintaining force closure and stability. Due to the complexity of modeling the contact dyna... |
DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality | https://ieeexplore.ieee.org/document/10160216/ | [
"Ankur Handa",
"Arthur Allshire",
"Viktor Makoviychuk",
"Aleksei Petrenko",
"Ritvik Singh",
"Jingzhou Liu",
"Denys Makoviichuk",
"Karl Van Wyk",
"Alexander Zhurkevich",
"Balakumar Sundaralingam",
"Yashraj Narang",
"Ankur Handa",
"Arthur Allshire",
"Viktor Makoviychuk",
"Aleksei Petrenko",
"Ritvik Singh",
"Jingzhou Liu",
"Denys Makoviichuk",
"Karl Van Wyk",
"Alexander Zhurkevich",
"Balakumar Sundaralingam",
"Yashraj Narang"
] | Recent work has demonstrated the ability of deep reinforcement learning (RL) algorithms to learn complex robotic behaviours in simulation, including in the domain of multi-fingered manipulation. However, such models can be challenging to transfer to the real world due to the gap between simulation and reality. In this paper, we present our techniques to train a) a policy that can perform robust de... |
Meta-Reinforcement Learning via Language Instructions | https://ieeexplore.ieee.org/document/10160626/ | [
"Zhenshan Bing",
"Alexander Koch",
"Xiangtong Yao",
"Kai Huang",
"Alois Knoll",
"Zhenshan Bing",
"Alexander Koch",
"Xiangtong Yao",
"Kai Huang",
"Alois Knoll"
] | Although deep reinforcement learning has recently been very successful at learning complex behaviors, it requires a tremendous amount of data to learn a task. One of the fundamental reasons causing this limitation lies in the nature of the trial-and-error learning paradigm of reinforcement learning, where the agent communicates with the environment and pro-gresses in the learning only relying on t... |
Improving Video Super-Resolution with Long-Term Self-Exemplars | https://ieeexplore.ieee.org/document/10160844/ | [
"Guotao Meng",
"Yue Wu",
"Qifeng Chen",
"Guotao Meng",
"Yue Wu",
"Qifeng Chen"
] | Existing video super-resolution methods often utilize a few neighboring frames to generate a higher-resolution image for each frame. However, the abundant information in distant frames has not been fully exploited in these methods: corresponding patches of the same instance appear across distant frames at different scales. Based on this observation, we propose to improve the video super-resolution... |
Learning-based Relational Object Matching Across Views | https://ieeexplore.ieee.org/document/10161393/ | [
"Cathrin Elich",
"Iro Armeni",
"Martin R. Oswald",
"Marc Pollefeys",
"Joerg Stueckler",
"Cathrin Elich",
"Iro Armeni",
"Martin R. Oswald",
"Marc Pollefeys",
"Joerg Stueckler"
] | Intelligent robots require object-level scene understanding to reason about possible tasks and interactions with the environment. Moreover, many perception tasks such as scene reconstruction, image retrieval, or place recognition can benefit from reasoning on the level of objects. While keypoint-based matching can yield strong results for finding correspondences for images with small to medium vie... |
TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detection in Aerial Videos | https://ieeexplore.ieee.org/document/10161433/ | [
"Tushar Sangam",
"Ishan Rajendrakumar Dave",
"Waqas Sultani",
"Mubarak Shah",
"Tushar Sangam",
"Ishan Rajendrakumar Dave",
"Waqas Sultani",
"Mubarak Shah"
] | Drone-to-drone detection using visual feed has crucial applications, such as detecting drone collisions, detecting drone attacks, or coordinating flight with other drones. However, existing methods are computationally costly, follow non-end-to-end optimization, and have complex multi-stage pipelines, making them less suitable for real-time deployment on edge devices. In this work, we propose a sim... |
Unsupervised RGB-to-Thermal Domain Adaptation via Multi-Domain Attention Network | https://ieeexplore.ieee.org/document/10160872/ | [
"Lu Gan",
"Connor Lee",
"Soon-Jo Chung",
"Lu Gan",
"Connor Lee",
"Soon-Jo Chung"
] | This work presents a new method for unsupervised thermal image classification and semantic segmentation by transferring knowledge from the RGB domain using a multi-domain attention network. Our method does not require any thermal annotations or co-registered RGB-thermal pairs, enabling robots to perform visual tasks at night and in adverse weather conditions without incurring additional costs of d... |
Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics | https://ieeexplore.ieee.org/document/10160551/ | [
"Adarsh Kumar Kosta",
"Kaushik Roy",
"Adarsh Kumar Kosta",
"Kaushik Roy"
] | Event-based cameras have recently shown great potential for high-speed motion estimation owing to their ability to capture temporally rich information asynchronously. Spiking Neural Networks (SNNs), with their neuro-inspired event-driven processing can efficiently handle such asynchronous data, while neuron models such as the leaky-integrate and fire (LIF) can keep track of the quintessential timi... |
Reinforced Learning for Label-Efficient 3D Face Reconstruction | https://ieeexplore.ieee.org/document/10161362/ | [
"Hoda Mohaghegh",
"Hossein Rahmani",
"Hamid Laga",
"Farid Boussaid",
"Mohammed Bennamoun",
"Hoda Mohaghegh",
"Hossein Rahmani",
"Hamid Laga",
"Farid Boussaid",
"Mohammed Bennamoun"
] | 3D face reconstruction plays a major role in many human-robot interaction systems, from automatic face authentication to human-computer interface-based entertainment. To improve robustness against occlusions and noise, 3D face reconstruction networks are often trained on a set of in-the-wild face images preferably captured along different viewpoints of the subject. However, collecting the required... |
Bridging the Domain Gap for Multi-Agent Perception | https://ieeexplore.ieee.org/document/10160871/ | [
"Runsheng Xu",
"Jinlong Li",
"Xiaoyu Dong",
"Hongkai Yu",
"Jiaqi Ma",
"Runsheng Xu",
"Jinlong Li",
"Xiaoyu Dong",
"Hongkai Yu",
"Jiaqi Ma"
] | Existing multi-agent perception algorithms usually select to share deep neural features extracted from raw sensing data between agents, achieving a trade-off between accuracy and communication bandwidth limit. However, these methods assume all agents have identical neural networks, which might not be practical in the real world. The transmitted features can have a large domain gap when the models ... |
UPLIFT: Unsupervised Person Labeling and Identification via Cooperative Learning with Mobile Robots | https://ieeexplore.ieee.org/document/10161103/ | [
"Yu-Chee Tseng",
"Ting-Yuan Ke",
"Fang–Jing Wu",
"Yu-Chee Tseng",
"Ting-Yuan Ke",
"Fang–Jing Wu"
] | As robots are widely used in assisting manual tasks, an interesting challenge is: Can mobile robots help create a labeled knowledge dataset that can be used for efficiently creating deep learning models for other sensors? This paper proposes an Unsupervised Person Labeling and Identification (UPLIFT) framework to automatically enlarge the labeled knowledge dataset. Typically, manual data labeling ... |
Learning to Explore Informative Trajectories and Samples for Embodied Perception | https://ieeexplore.ieee.org/document/10160951/ | [
"Ya Jing",
"Tao Kong",
"Ya Jing",
"Tao Kong"
] | We are witnessing significant progress on perception models, specifically those trained on large-scale internet images. However, efficiently generalizing these perception models to unseen embodied tasks is insufficiently studied, which will help various relevant applications (e.g., home robots). Unlike static perception methods trained on pre-collected images, the embodied agent can move around in... |
Embodied Agents for Efficient Exploration and Smart Scene Description | https://ieeexplore.ieee.org/document/10160668/ | [
"Roberto Bigazzi",
"Marcella Cornia",
"Silvia Cascianelli",
"Lorenzo Baraldi",
"Rita Cucchiara",
"Roberto Bigazzi",
"Marcella Cornia",
"Silvia Cascianelli",
"Lorenzo Baraldi",
"Rita Cucchiara"
] | The development of embodied agents that can communicate with humans in natural language has gained increasing interest over the last years, as it facilitates the diffusion of robotic platforms in human-populated environments. As a step towards this objective, in this work, we tackle a setting for visual navigation in which an autonomous agent needs to explore and map an unseen indoor environment w... |
Deep Neural Network Architecture Search for Accurate Visual Pose Estimation aboard Nano-UAVs | https://ieeexplore.ieee.org/document/10160369/ | [
"E. Cereda",
"L. Crupi",
"M. Risso",
"A. Burrello",
"L. Benini",
"A. Giusti",
"D. Jahier Pagliari",
"D. Palossi",
"E. Cereda",
"L. Crupi",
"M. Risso",
"A. Burrello",
"L. Benini",
"A. Giusti",
"D. Jahier Pagliari",
"D. Palossi"
] | Miniaturized autonomous unmanned aerial vehicles (UAVs) are an emerging and trending topic. With their form factor as big as the palm of one hand, they can reach spots otherwise inaccessible to bigger robots and safely operate in human surroundings. The simple electronics aboard such robots (sub-100 mW) make them particularly cheap and attractive but pose significant challenges in enabling onboard... |
Reuse your features: unifying retrieval and feature-metric alignment | https://ieeexplore.ieee.org/document/10160501/ | [
"Javier Morlana",
"J.M.M. Montiel",
"Javier Morlana",
"J.M.M. Montiel"
] | We propose a compact pipeline to unify all the steps of Visual Localization: image retrieval, candidate re-ranking and initial pose estimation, and camera pose refinement. Our key assumption is that the deep features used for these individual tasks share common characteristics, so we should reuse them in all the procedures of the pipeline. Our DRAN (Deep Retrieval and image Alignment Network) is a... |
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions from Single Panoramas | https://ieeexplore.ieee.org/document/10161142/ | [
"Bruno Berenguel-Baeta",
"Jesus Bermudez-Cameo",
"Jose J. Guerrero",
"Bruno Berenguel-Baeta",
"Jesus Bermudez-Cameo",
"Jose J. Guerrero"
] | In this work we present FreDSNet, a deep learning solution which obtains semantic 3D understanding of indoor environments from single panoramas. Omnidirectional images reveal task-specific advantages when addressing scene understanding problems due to the 360-degree contextual information about the entire environment they provide. However, the inherent characteristics of the omnidirectional images... |
CAHIR: Co-Attentive Hierarchical Image Representations for Visual Place Recognition | https://ieeexplore.ieee.org/document/10160512/ | [
"Guohao Peng",
"Heshan Li",
"Yifeng Huang",
"Jun Zhang",
"Mingxing Wen",
"Singh Rahul",
"Danwei Wang",
"Guohao Peng",
"Heshan Li",
"Yifeng Huang",
"Jun Zhang",
"Mingxing Wen",
"Singh Rahul",
"Danwei Wang"
] | Robust visual place recognition (VPR) against significant appearance changes is crucial for the life-long operation of mobile robots. Focusing on this task, we propose a Co-Attentive Hierarchical Image Representations (CAHIR) framework for VPR, which unifies attention-sharing global and local descriptor generation into one encoding pipeline. The hierarchical descriptors are applied to a coarse-to-... |
Monocular Visual-Inertial Depth Estimation | https://ieeexplore.ieee.org/document/10161013/ | [
"Diana Wofk",
"René Ranftl",
"Matthias Müller",
"Vladlen Koltun",
"Diana Wofk",
"René Ranftl",
"Matthias Müller",
"Vladlen Koltun"
] | We present a visual-inertial depth estimation pipeline that integrates monocular depth estimation and visual- inertial odometry to produce dense depth estimates with metric scale. Our approach performs global scale and shift alignment against sparse metric depth, followed by learning-based dense alignment. We evaluate on the TartanAir and VOID datasets, observing up to 30% reduction in inverse RMS... |
KGNet: Knowledge-Guided Networks for Category-Level 6D Object Pose and Size Estimation | https://ieeexplore.ieee.org/document/10160349/ | [
"Qiwei Meng",
"Jason Gu",
"Shiqiang Zhu",
"Jianfeng Liao",
"Tianlei Jin",
"Fangtai Guo",
"Wen Wang",
"Wei Song",
"Qiwei Meng",
"Jason Gu",
"Shiqiang Zhu",
"Jianfeng Liao",
"Tianlei Jin",
"Fangtai Guo",
"Wen Wang",
"Wei Song"
] | Despite the giant leap made in object 6D pose estimation and robotic grasping under structured scenarios, most approaches depend heavily on the exact CAD models of target objects beforehand, thereby limiting their wide applications. To address this, we propose a novel knowledge-guided network - KGNet to estimate the pose and size of category-level unseen objects. This network includes three primar... |
Online Consistent Video Depth with Gaussian Mixture Representation | https://ieeexplore.ieee.org/document/10160785/ | [
"Chao Liu",
"Benjamin Eckart",
"Jan Kautz",
"Chao Liu",
"Benjamin Eckart",
"Jan Kautz"
] | We demonstrate how off-the-shelf single-image depth estimation methods can be augmented with guidance from optical flow to achieve consistent and accurate online depth estimation using video sequences of static scenes. While previous work has successfully leveraged the complementary nature of optical flow and depth estimation, these techniques use computationally expensive test time optimization s... |
Deep Masked Graph Matching for Correspondence Identification in Collaborative Perception | https://ieeexplore.ieee.org/document/10161231/ | [
"Peng Gao",
"Qingzhao Zhu",
"Hongsheng Lu",
"Chuang Gan",
"Hao Zhang",
"Peng Gao",
"Qingzhao Zhu",
"Hongsheng Lu",
"Chuang Gan",
"Hao Zhang"
] | Correspondence identification (CoID) is an essential component for collaborative perception in multi-robot systems, such as connected autonomous vehicles. The goal of CoID is to identify the correspondence of objects observed by multiple robots in their own field of view in order for robots to consistently refer to the same objects. CoID is challenging due to perceptual aliasing, object non-covisi... |
Operative Action Captioning for Estimating System Actions | https://ieeexplore.ieee.org/document/10161545/ | [
"Taiki Nakamura",
"Seiya Kawano",
"Akishige Yuguchi",
"Yasutomo Kawanishi",
"Koichiro Yoshino",
"Taiki Nakamura",
"Seiya Kawano",
"Akishige Yuguchi",
"Yasutomo Kawanishi",
"Koichiro Yoshino"
] | Human-assistive systems, such as robots, need to correctly understand the surrounding situation based on obser-vations and output the required support actions for humans. Language is one of the important channels to communicate with humans, and robots are required to have the ability to express their understanding and action-planning results. In this study, we propose a new task of operative actio... |
Deep Unsupervised Visual Odometry Via Bundle Adjusted Pose Graph Optimization | https://ieeexplore.ieee.org/document/10160703/ | [
"Guoyu Lu",
"Guoyu Lu"
] | Unsupervised visual odometry as an active topic has attracted extensive attention, benefiting from its label-free practical value and robustness in real-world scenarios. However, the performance of camera pose estimation and tracking through deep neural network is still not as ideal as most other tasks, such as detection, segmentation and depth estimation, due to the lack of drift correction in th... |
Pose Relation Transformer Refine Occlusions for Human Pose Estimation | https://ieeexplore.ieee.org/document/10161259/ | [
"Hyung-gun Chi",
"Seunggeun Chi",
"Stanley Chan",
"Karthik Ramani",
"Hyung-gun Chi",
"Seunggeun Chi",
"Stanley Chan",
"Karthik Ramani"
] | Accurately estimating the human pose is an essential task for many applications in robotics. However, existing pose estimation methods suffer from poor performance when occlusion occurs. Recent advances in NLP have been very successful in predicting the missing words conditioned on visible words. We draw upon the sentence completion analogy in NLP to guide our model to address occlusions in the po... |
Question Generation for Uncertainty Elimination in Referring Expressions in 3D Environments | https://ieeexplore.ieee.org/document/10160386/ | [
"Fumiya Matsuzawa",
"Yue Qiu",
"Kenji Iwata",
"Hirokatsu Kataoka",
"Yutaka Satoh",
"Fumiya Matsuzawa",
"Yue Qiu",
"Kenji Iwata",
"Hirokatsu Kataoka",
"Yutaka Satoh"
] | We introduce a new task of question generation to eliminate the uncertainty of referring expressions in 3D indoor environments (3D-REQ). Referring to an object using natural language is one of the most common occurrences in daily human conversations; therefore, instructing robots to identify a certain object using natural language could be an essential task in var-ious robotic applications, such a... |
A New Efficient Eye Gaze Tracker for Robotic Applications | https://ieeexplore.ieee.org/document/10161347/ | [
"Chaitanya Bandi",
"Ulrike Thomas",
"Chaitanya Bandi",
"Ulrike Thomas"
] | Gaze estimation provides insight into a person's intent and engagement level, which is helpful in collaborative human-robot applications. With significant advancements in deep learning architectures, appearance-based gaze estimation has gained much attention. Appearance-based methods have shown significant improvement in gaze accuracy and, unlike traditional approaches, they function well in envir... |
A Deep Learning Human Activity Recognition Framework for Socially Assistive Robots to Support Reablement of Older Adults | https://ieeexplore.ieee.org/document/10161404/ | [
"Fraser Robinson",
"Goldie Nejat",
"Fraser Robinson",
"Goldie Nejat"
] | Many older adults prefer to stay in their own homes and age-in-place. However, physical and cognitive limitations in independently completing activities of daily living (ADLs) requires older adults to receive assistive support, often necessitating transitioning to care centers. In this paper, we present the development of a novel deep learning human activity recognition and classification architec... |
FloorplanNet: Learning Topometric Floorplan Matching for Robot Localization | https://ieeexplore.ieee.org/document/10160977/ | [
"Delin Feng",
"Zhenpeng He",
"Jiawei Hou",
"Sören Schwertfeger",
"Liangjun Zhang",
"Delin Feng",
"Zhenpeng He",
"Jiawei Hou",
"Sören Schwertfeger",
"Liangjun Zhang"
] | Given a building floorplan, humans can localize themselves by matching the observation of the environment with the floorplan using geometric, semantic, and topological clues. Inspired by this insight, this paper proposes a learning- based topometric robot localization method FloorplanNet, which implements a match between a metric robot map and the potentially inaccurate building floorplan in nonun... |
MOFT: Monocular odometry based on deep depth and careful feature selection and tracking | https://ieeexplore.ieee.org/document/10160588/ | [
"Karlo Koledić",
"Igor Cvišić",
"Ivan Marković",
"Ivan Petrović",
"Karlo Koledić",
"Igor Cvišić",
"Ivan Marković",
"Ivan Petrović"
] | Autonomous localization in unknown environments is a fundamental problem in many emerging fields and the monocular visual approach offers many advantages, due to being a rich source of information and avoiding comparatively more complicated setups and multisensor calibration. Deep learning opened new venues for monocular odometry yielding not only end-to-end approaches but also hybrid methods comb... |
LGCNet: Feature Enhancement and Consistency Learning Based on Local and Global Coherence Network for Correspondence Selection | https://ieeexplore.ieee.org/document/10160290/ | [
"Tzu-Han Wu",
"Kuan-Wen Chen",
"Tzu-Han Wu",
"Kuan-Wen Chen"
] | Correspondence selection, a crucial step in many computer vision tasks, aims to distinguish between inliers and outliers from putative correspondences. The coherence of correspondences is often used for predicting inlier probability, but it is difficult for neural networks to extract coherence contexts based only on quadruple coordinates. To overcome this difficulty, we propose enhancing the preli... |
Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors | https://ieeexplore.ieee.org/document/10161381/ | [
"Hao Dong",
"Xieyuanli Chen",
"Mihai Dusmanu",
"Viktor Larsson",
"Marc Pollefeys",
"Cyrill Stachniss",
"Hao Dong",
"Xieyuanli Chen",
"Mihai Dusmanu",
"Viktor Larsson",
"Marc Pollefeys",
"Cyrill Stachniss"
] | A distinctive representation of image patches in form of features is a key component of many computer vision and robotics tasks, such as image matching, image retrieval, and visual localization. State-of-the-art descriptors, from hand-crafted descriptors such as SIFT to learned ones such as HardNet, are usually high-dimensional; 128 dimensions or even more. The higher the dimensionality, the large... |
Online Visual SLAM Adaptation against Catastrophic Forgetting with Cycle-Consistent Contrastive Learning | https://ieeexplore.ieee.org/document/10161464/ | [
"Sangni Xu",
"Hao Xiong",
"Qiuxia Wu",
"Tingting Yao",
"Zhihui Wang",
"Zhiyong Wang",
"Sangni Xu",
"Hao Xiong",
"Qiuxia Wu",
"Tingting Yao",
"Zhihui Wang",
"Zhiyong Wang"
] | Visual SLAM (Simultaneous Localisation and Mapping) aims to simultaneously estimate camera poses and depth maps from navigation videos captured. While recent deep learning based methods have achieved great success on this task, they tend to work well on source domain data and suffer from performance degradation on the unseen data of target domain. Hence, we propose an online adaptation approach to... |
SLAMER: Simultaneous Localization and Map-Assisted Environment Recognition | https://ieeexplore.ieee.org/document/10160639/ | [
"Naoki Akai",
"Naoki Akai"
] | This paper presents a simultaneous localization and map-assisted environment recognition (SLAMER) method. Mobile robots usually have an environment map and environment information can be assigned to the map. Important information such as no entry zone can be predicted from the map if localization has succeeded. However, this prediction is failed when localization does not work. Uncertainty of pose... |
Descriptor Distillation for Efficient Multi-Robot SLAM | https://ieeexplore.ieee.org/document/10160541/ | [
"Xiyue Guo",
"Junjie Hu",
"Hujun Bao",
"Guofeng Zhang",
"Xiyue Guo",
"Junjie Hu",
"Hujun Bao",
"Guofeng Zhang"
] | Performing accurate localization while maintaining the low-level communication bandwidth is an essential challenge of multi-robot simultaneous localization and mapping (MR-SLAM). In this paper, we tackle this problem by generating a compact yet discriminative feature descriptor with minimum inference time. We propose descriptor distillation that formulates the descriptor generation into a learning... |
DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory | https://ieeexplore.ieee.org/document/10160364/ | [
"Juyeop Han",
"Youngjae Min",
"Hyeok-Joo Chae",
"Byeong-Min Jeong",
"Han-Lim Choi",
"Juyeop Han",
"Youngjae Min",
"Hyeok-Joo Chae",
"Byeong-Min Jeong",
"Han-Lim Choi"
] | Occupancy mapping has been widely utilized to represent the surroundings for autonomous robots to perform tasks such as navigation and manipulation. While occupancy mapping in 2-D environments has been well-studied, there have been few approaches suitable for 3-D dynamic occupancy mapping which is essential for aerial robots. This paper presents a novel 3-D dynamic occupancy mapping algorithm call... |
Monocular Visual-Inertial Odometry with Planar Regularities | https://ieeexplore.ieee.org/document/10160620/ | [
"Chuchu Chen",
"Patrick Geneva",
"Yuxiang Peng",
"Woosik Lee",
"Guoquan Huang",
"Chuchu Chen",
"Patrick Geneva",
"Yuxiang Peng",
"Woosik Lee",
"Guoquan Huang"
] | State-of-the-art monocular visual-inertial odometry (VIO) approaches rely on sparse point features in part due to their efficiency, robustness, and prevalence, while ignoring high-level structural regularities such as planes that are common to man-made environments and can be exploited to further constrain motion. Generally, planes can be observed by a camera for significant periods of time due to... |
BAMF-SLAM: Bundle Adjusted Multi-Fisheye Visual-Inertial SLAM Using Recurrent Field Transforms | https://ieeexplore.ieee.org/document/10160905/ | [
"Wei Zhang",
"Sen Wang",
"Xingliang Dong",
"Rongwei Guo",
"Norbert Haala",
"Wei Zhang",
"Sen Wang",
"Xingliang Dong",
"Rongwei Guo",
"Norbert Haala"
] | In this paper, we present BAMF-SLAM, a novel multi-fisheye visual-inertial SLAM system that utilizes Bundle Adjustment (BA) and recurrent field transforms (RFT) to achieve accurate and robust state estimation in challenging scenarios. First, our system directly operates on raw fisheye images, enabling us to fully exploit the wide Field-of-View (FoV) of fisheye cameras. Second, to overcome the low-... |
Improving the Performance of Local Bundle Adjustment for Visual-Inertial SLAM with Efficient Use of GPU Resources | https://ieeexplore.ieee.org/document/10160499/ | [
"Shishir Gopinath",
"Karthik Dantu",
"Steven Y. Ko",
"Shishir Gopinath",
"Karthik Dantu",
"Steven Y. Ko"
] | In this paper, we present our approach to efficiently leveraging GPU resources to improve the performance of local bundle adjustment for visual-inertial SLAM. We observe that for local bundle adjustment (i) the Schur complement method, a technique often used to speed up bundle adjustment, has the largest overhead when solving for the parameter update, and (ii) the workload consists of operations o... |
Distributed Initialization for Visual-Inertial-Ranging Odometry with Position-Unknown UWB Network | https://ieeexplore.ieee.org/document/10161382/ | [
"Shenhan Jia",
"Rong Xiong",
"Yue Wang",
"Shenhan Jia",
"Rong Xiong",
"Yue Wang"
] | In recent years, the visual-inertial-ranging (VIR) state estimator with a position-unknown UWB network has become popular. However, most existing VIR methods leverage centralized algorithms to initialize the UWB anchors, which are challenging to be applied to massive UWB networks. In this paper, we propose a distributed initialization method for consistent visual-inertial-ranging odometry with a p... |
Automating Vascular Shunt Insertion with the dVRK Surgical Robot | https://ieeexplore.ieee.org/document/10160966/ | [
"Karthik Dharmarajan",
"Will Panitch",
"Muyan Jiang",
"Kishore Srinivas",
"Baiyu Shi",
"Yahav Avigal",
"Huang Huang",
"Thomas Low",
"Danyal Fer",
"Ken Goldberg",
"Karthik Dharmarajan",
"Will Panitch",
"Muyan Jiang",
"Kishore Srinivas",
"Baiyu Shi",
"Yahav Avigal",
"Huang Huang",
"Thomas Low",
"Danyal Fer",
"Ken Goldberg"
] | Vascular shunt insertion is a fundamental surgical procedure used to temporarily restore blood flow to tissues. It is often performed in the field after major trauma. We formulate a problem of automated vascular shunt insertion and propose a pipeline to perform Automated Vascular Shunt Insertion (AVSI) using a da Vinci Research Kit. The pipeline uses a learned visual model to estimate the locus of... |
CogniDaVinci: Towards Estimating Mental Workload Modulated by Visual Delays During Telerobotic Surgery - An EEG-based Analysis | https://ieeexplore.ieee.org/document/10161007/ | [
"Satyam Kumar",
"Deland H. Liu",
"Frigyes S. Racz",
"Manuel Retana",
"Susheela Sharma",
"Fumiaki Iwane",
"Braden P. Murphy",
"Rory O'Keeffe",
"S. Farokh Atashzar",
"Farshid Alambeigi",
"José del R. Millán",
"Satyam Kumar",
"Deland H. Liu",
"Frigyes S. Racz",
"Manuel Retana",
"Susheela Sharma",
"Fumiaki Iwane",
"Braden P. Murphy",
"Rory O'Keeffe",
"S. Farokh Atashzar",
"Farshid Alambeigi",
"José del R. Millán"
] | Communication latency in any delicate telerobotic operation (such as remote surgery over distance) would impose a significant challenge due to the temporal degradation of visual perception and can substantially affect the outcomes. Less is known, however, about the neurophysiological basis of how operators adapt/react to delayed visual feedback. Identification of such neural markers might provide ... |
Exploring An External Approach to Subretinal Drug Delivery via Robot Assistance and B-Mode OCT | https://ieeexplore.ieee.org/document/10161441/ | [
"Elan Z. Ahronovich",
"Neel Shihora",
"Jin-Hui Shen",
"Karen Joos",
"Nabil Simaan",
"Elan Z. Ahronovich",
"Neel Shihora",
"Jin-Hui Shen",
"Karen Joos",
"Nabil Simaan"
] | Injections into specific retinal layers of the eye present a serious challenge to surgeons in terms of accuracy and perception. The emergence of new gene therapies further emphasizes the need for effective tools for localized drug delivery. Unlike the dominant approach of delivering drugs via a transvitreal intraocular pathway, this paper demonstrates the feasibility of delivering injections into ... |
Towards Surgical Context Inference and Translation to Gestures | https://ieeexplore.ieee.org/document/10160383/ | [
"Kay Hutchinson",
"Zongyu Li",
"Ian Reyes",
"Homa Alemzadeh",
"Kay Hutchinson",
"Zongyu Li",
"Ian Reyes",
"Homa Alemzadeh"
] | Manual labeling of gestures in robot-assisted surgery is labor intensive, prone to errors, and requires expertise or training. We propose a method for automated and explainable generation of gesture transcripts that leverages the abundance of data for image segmentation. Surgical context is detected using segmentation masks by examining the distances and intersections between the tools and objects... |
A Method to Use Haptic Feedback of Laryngoscope Force Vector for Endotracheal Intubation Training | https://ieeexplore.ieee.org/document/10160755/ | [
"Haonan Zhou",
"Siyu Yang",
"Lou Halamek",
"Thrishantha Nanayakkara",
"Haonan Zhou",
"Siyu Yang",
"Lou Halamek",
"Thrishantha Nanayakkara"
] | Endotracheal intubation is a mandatory competency for most medical staff. This procedure involves opening the entrance of the patient's upper windpipe using a laryngoscope and then inserting a tube into the windpipe to supply Oxygen to the patient. This time critical intervention requires careful control of the force vector on the tongue to lift it parallel to the jaw than to push the jaw to open ... |
A hydraulic soft robotic detrusor based on an origami design | https://ieeexplore.ieee.org/document/10160652/ | [
"Simone Onorati",
"Federica Semproni",
"Linda Paternò",
"Giada Casagrande",
"Veronica Iacovacci",
"Arianna Menciassi",
"Simone Onorati",
"Federica Semproni",
"Linda Paternò",
"Giada Casagrande",
"Veronica Iacovacci",
"Arianna Menciassi"
] | As a permanent solution for patients who cannot contract their urinary bladder, an artificial detrusor muscle appears a higher outcome approach compared to current sacral neurostimulators featured by severe long-term side effects. In this paper, a novel soft robotic detrusor is presented to overcome the limitations of the state-of-the-art solutions. It is based on two identical origami-based hydra... |
Semi-autonomous robotic control of a self-shaping cochlear implant | https://ieeexplore.ieee.org/document/10161565/ | [
"Daniel Bautista-Salinas",
"Conor Kirby",
"Mohamed E. M. K. Abdelaziz",
"Burak Temelkuran",
"Charlie T. Huins",
"Ferdinando Rodriguez y Baena",
"Daniel Bautista-Salinas",
"Conor Kirby",
"Mohamed E. M. K. Abdelaziz",
"Burak Temelkuran",
"Charlie T. Huins",
"Ferdinando Rodriguez y Baena"
] | Cochlear implants (CIs) can improve hearing in patients suffering from sensorineural hearing loss via an electrode array (EA) carefully inserted in the scala tympani. Current EAs can cause trauma during insertion, threatening hearing preservation; hence we proposed a pre-curved thermally drawn EA that curls into the cochlea under the influence of body temperature. However, the additional surgical ... |
A Hybrid Steerable Robot with Magnetic Wrist for Minimally Invasive Epilepsy Surgery | https://ieeexplore.ieee.org/document/10160446/ | [
"Changyan He",
"Robert H. Nguyen",
"Cameron Forbrigger",
"James Drake",
"Thomas Looi",
"Eric Diller",
"Changyan He",
"Robert H. Nguyen",
"Cameron Forbrigger",
"James Drake",
"Thomas Looi",
"Eric Diller"
] | Dexterity is demanded for an endoscopic tool to handle complicated procedures in neurosurgery, e.g., removing diseased tissue from inside the deep brain along a tortuous path. Current robotic tools are either rigid or lack wristed motion ability at the tip, leading to limited usage in minimally invasive procedures. In this paper, a hybrid steerable robot with a magnetic wristed forceps is proposed... |
Induced Vertex Motion As a Performance Measure for Surgery in Confined Spaces | https://ieeexplore.ieee.org/document/10161512/ | [
"Neel Shihora",
"Nabil Simaan",
"Neel Shihora",
"Nabil Simaan"
] | While in the design phase of a robotic system for the procedures performed in surgical confined spaces or hard-to-reach-deep surgical fields, designers can leverage a systematic method to compare the design alternatives for tele-surgical manipulators quantitatively. Unlike most of the work in the literature, we propose an approach for comparing design alternatives by considering the spurious motio... |
Foot gestures to control the grasping of a surgical robot | https://ieeexplore.ieee.org/document/10160368/ | [
"Yijun Cheng",
"Yanpei Huang",
"Ziwei Wang",
"Etienne Burdet",
"Yijun Cheng",
"Yanpei Huang",
"Ziwei Wang",
"Etienne Burdet"
] | Many surgical tasks require three or more tools working together, where a hands-free interface could extend a surgeon's actions to control a third surgical tool. However, most current interfaces do not allow skilled control of grasping critical to robotic manipulation. Here we first present a systematic study to identify efficient and intuitive interaction strategies to control grasping of a surgi... |
Design and Development of a Novel Force-Sensing Robotic System for the Transseptal Puncture in Left Atrial Catheter Ablation | https://ieeexplore.ieee.org/document/10160254/ | [
"Aya Mutaz Zeidan",
"Zhouyang Xu",
"Christopher E. Mower",
"Honglei Wu",
"Quentin Walker",
"Oyinkansola Ayoade",
"Natalia Cotic",
"Jonathan Behar",
"Steven Williams",
"Aruna Arujuna",
"Yohan Noh",
"Richard Housden",
"Kawal Rhode",
"Aya Mutaz Zeidan",
"Zhouyang Xu",
"Christopher E. Mower",
"Honglei Wu",
"Quentin Walker",
"Oyinkansola Ayoade",
"Natalia Cotic",
"Jonathan Behar",
"Steven Williams",
"Aruna Arujuna",
"Yohan Noh",
"Richard Housden",
"Kawal Rhode"
] | Transseptal puncture (TSP) is a prerequisite for left atrial catheter ablation for atrial fibrillation, requiring access from the right side of the heart. It is a demanding procedural step associated with complications, including inadvertent puncturing and application of large forces on the tissue wall. Robotic systems have shown great potential to overcome such challenges by introducing force-sen... |
Surgical-VQLA:Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery | https://ieeexplore.ieee.org/document/10160403/ | [
"Long Bai",
"Mobarakol Islam",
"Lalithkumar Seenivasan",
"Hongliang Ren",
"Long Bai",
"Mobarakol Islam",
"Lalithkumar Seenivasan",
"Hongliang Ren"
] | Despite the availability of computer-aided simulators and recorded videos of surgical procedures, junior residents still heavily rely on experts to answer their queries. However, expert surgeons are often overloaded with clinical and academic workloads and limit their time in answering. For this purpose, we develop a surgical question-answering system to facilitate robot-assisted surgical scene an... |
Implicit Neural Field Guidance for Teleoperated Robot-assisted Surgery | https://ieeexplore.ieee.org/document/10160475/ | [
"Heng Zhang",
"Lifeng Zhu",
"Jiangwei Shen",
"Aiguo Song",
"Heng Zhang",
"Lifeng Zhu",
"Jiangwei Shen",
"Aiguo Song"
] | Teleoperated techniques enable remote human-robot interaction and have been widely accepted in robot-assisted surgeries. However, it is still hard to guarantee the safety of teleoperated surgery due to the imperfect input commands limited by remote perception, preventing teleoperated surgery from being widely used. We propose a new framework to avoid the collision of surgery robots and human tissu... |
Bidirectional Generalised Rigid Point Set Registration | https://ieeexplore.ieee.org/document/10160361/ | [
"Ang Zhang",
"Zhe Min",
"Li Liu",
"Max Q.-H. Meng",
"Ang Zhang",
"Zhe Min",
"Li Liu",
"Max Q.-H. Meng"
] | In medical robotics and image-guided surgery (IGS), registration is needed in order to align together the coordinate frames of robots, medical imaging modalities, surgical tools, and patients. Existing registration algorithms often assume one point set to be a noise-free model while the other to contain noise and outliers. However, in real scenarios, noise and outliers can exist in both point sets... |
Finding the Optimal Incision Point in Robotic Assisted Surgery | https://ieeexplore.ieee.org/document/10160936/ | [
"Kyriakos Almpanidis",
"Theodora Kastritsi",
"Zoe Doulgeri",
"Kyriakos Almpanidis",
"Theodora Kastritsi",
"Zoe Doulgeri"
] | In robotic assisted surgeries, surgical tools are inserted into the human body via an incision point in the abdominal wall, which is imposed as a remote center of motion (RCM). The selection of the incision's point location in the human body is critical for the success of the surgical procedure. In this paper, we propose a simulation tool for finding the optimal incision point location, which can ... |
Development and Experimental Verification of a 3D Dynamic Absolute Nodal Coordinate Formulation Model of Flexible Prostate Biopsy/Brachytherapy Needles | https://ieeexplore.ieee.org/document/10161254/ | [
"Athanasios Martsopoulos",
"Thomas L. Hill",
"Rajendra Persad",
"Stefanos Bolomytis",
"Antonia Tzemanaki",
"Athanasios Martsopoulos",
"Thomas L. Hill",
"Rajendra Persad",
"Stefanos Bolomytis",
"Antonia Tzemanaki"
] | Robot-assisted percutaneous needle insertion is expected to significantly increase targeting accuracy in minimally invasive operations. For this, it is necessary to provide mathematical models that can accurately capture the underlying dynamics of medical needles. Here, we present a novel nonlinear mathematical model of flexible medical needles based on the Absolute Nodal Coordinate Formulation. T... |
Collaborative Robotic Biopsy with Trajectory Guidance and Needle Tip Force Feedback | https://ieeexplore.ieee.org/document/10161377/ | [
"Robin Mieling",
"Maximilian Neidhardt",
"Sarah Latus",
"Carolin Stapper",
"Stefan Gerlach",
"Inga Kniep",
"Axel Heinemann",
"Benjamin Ondruschka",
"Alexander Schlaefer",
"Robin Mieling",
"Maximilian Neidhardt",
"Sarah Latus",
"Carolin Stapper",
"Stefan Gerlach",
"Inga Kniep",
"Axel Heinemann",
"Benjamin Ondruschka",
"Alexander Schlaefer"
] | The diagnostic value of biopsies is highly dependent on the placement of needles. Robotic trajectory guidance has been shown to improve needle positioning, but feedback for real-time navigation is limited. Haptic display of needle tip forces can provide rich feedback for needle navigation by enabling localization of tissue structures along the insertion path. We present a collaborative robotic bio... |
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